一种改进的基于峰值信噪比-高阶奇异值分解的天波超视距雷达自适应海杂波抑制算法

A Modified Adaptive Sea Clutter Suppression Algorithm Based on PSNR-HOSVD for Skywave OTHR

天波超视距雷达(OTHR)舰船目标的检测性能受目标区海杂波的影响严重,准确且自适应的海杂波抑制效能对改善低可探测舰船目标的检测性能意义重大。该文针对基于高阶奇异值分解(HOSVD)的海杂波抑制算法非自适应机制的不足,通过引入峰值信噪比(PSNR),提出一种改进的基于PSNR-HOSVD的自适应算法。该算法仅利用第3等效模式展开矩阵的左奇异向量构造一个投影矩阵,相比于HOSVD算法,该文算法可有效降低计算复杂度,同时由于海杂波仅在第3等效模式展开矩阵的列空间中具有聚集特性,因此该文算法具有比HOSVD算法更好的海杂波抑制性能。实测数据处理结果表明,在电离层状态理想和非理想的情况下,该文PSNR-HOSVD自适应算法的性能均优于EVD自适应算法和HOSVD非自适应算法。

The detection performance of ship targets by skywave Over-The-Horizon Radar (OTHR) is affected by the sea clutter seriously.Accurate and adaptive suppression of sea clutter is significant for improving the detection performance of ship target.To solve the non-adaptive shortness of the sea clutter suppression algorithm based on High-Order Singular Value Decomposition (HOSVD),a modified adaptive algorithm based on Peak Signal-to-Noise Ratio (PSNR)-HOSVD is proposed by introducing the PSNR.The modified algorithm has a smaller computational complexity than the one based on HOSVD,since only one projection matrix is established from the left singular vectors of the third-mode unfolding matrix.Meanwhile,the modified algorithm has a better performance than the HOSVD based one,because the components of sea clutter are only aggregated in the column space of the third-mode unfolding matrix.Experimental results based on two sets of measured data received in ideal and non-ideal situations in respective show that,the modified adaptive algorithm based on PSNR-HOSVD has a better performance than the peer algorithms.